EAGER: NSF2026: From Thinking to Inventing: Towards Creative Agents that Discover Novelty and Learn how to Accommodate it

Tufts University, Medford MA

Investigators

Abstract

While recent successes demonstrate the potential of artificial intelligence (AI) technologies, there are tenacious challenges left to address before AI programs will be able to reach the cognitive flexibility and sophistication of the human mind. One of the most pressing problems is how to deal with the unknown, with novel contexts or aspects of the world for which an AI system was not originally designed. Such "open-world" AI is still in its infancy and existing AI techniques do not easily transfer to open worlds. The goal of this project is to investigate ways in which AI agents can be endowed with creative problem-solving skills that allow them to negotiate open worlds and invent new tools, concepts, and eventually theories. Such a system could be the next major disruptive technology in AI, enabling not only long-term autonomy and resilience of robots in the light of faults and unexpected events, but more importantly, providing technology that could accelerate the solution of pressing problems that humanity is currently able to solve only slowly, if at all. Current AI algorithms rely on having complete models of the task and domain in which they are supposed to operate. If information is missing, they are not able to plan how to acquire it and extend their knowledge. Yet, systems that can determine that they are missing critical knowledge could use that information to guide their knowledge acquisition process and possibly develop creative approaches for inventing new tools and theories. This project will develop an integrated problem-solving system that adapts and incorporates different learning techniques and deploys each of these methods in a targeted fashion based on the problem aspect the approach is best equipped to solve. This system will be extended with the ability to apply different strategies for experimenting (just like humans) with objects in its environment to discover their properties and the actions that can be performed with those objects to build up new knowledge about objects and their functions. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.